Monday, June 13, 2016

Five Digital Epistemological Objects for 2064orA Digital Narrative Ark of the Knower

jon crowcroft, Cambridge, 8.5.2014

dreams, visions and prophecies in bits

It is too hard for humans to fully comprehend humans, but it may be possibleto construct a digital model, a computer simulation or even emulation,that is accurate, not just descriptive, but also predictive. Such amodel would embody modes of thinking that are not entirely rational,which is what current "AIs" attempt, but would extend to domainswhich, I believe, are entirely human, such as dreaming and visionaryor prophetic processes - these are not magic, or pseudo-science ideas,but ways in which human thought processes leapfrog piecewise orincremental steps, perhaps building on such mundane stages, but onlyrevealing themselves thus-wise, as revelations. Not blue gene beatinghumans at chess, but more surprising.

computational ethics

We struggle with ethical dilemmas. Why? there are ambiguities orparadoxes. These are quite easy to express in the right formalsystems, so we should be able to create, perhaps with help frommachines, ethical props, crutches, to help guide us to what is right.Asimov laws of robotics (4 in the end) were naive, but a start - weshould play with more such. The history of robots (golems, rossum'suniversal, mary shelley's etc) is littered with great examples.

diseases who think

it is a high pomp of pretentiousness that only humans think. we know(e.g. from Dunbar's (and Alison Richards') studies of apes)that the theory of mind is present to some degree in other creatures,and sometime, less so in some people.But the most alien of creatures, such as hive animals, and,in extremis, bacteria are capable of collective reasoning. Can wetrain them to help us? Can weinfect people with thoughts, literally, rather than merelyfiguratively?

smells, and superstitions, influence us and resonate more than carefulabstract recollections. Perhaps there's an embodiment of knowledge inthese modalities that we could build better, artificially, thanalready exist. Can we code ghosts?

learning to un-banish ghosts might be the ultimate rationalisation.

embodiment of knowing in the knower, is in some cases physiological(scent, muscle memory, belief) - capturing this missing element (where ourtypical current digital media representations address typically only 2or 3 (sight, hearing, perhaps touch) of the more boring senses, seemslike a worthy goal in terms of understanding our understanding moredeeply.

frailty -

we need digital analogues for flakiness - just as digitaltransmission of moving pictures can "degrade gracefully", perhapsknowledge can be coded in ways that can still be usefull when partlyrotten - as with the human suffering from dementia, still able to carryout some cognitive tasks, perhaps artificial thinking can be maderesilient. [today's programs, if even slightly corrupt, simply workthen fail - this is a poor show].

In a deeper sense, reflection on the inherent inaccuracy of representationis needed, etc

indeed, the optical metaphor can be (over-)extended, using the notionof different lenses, not just for different viewpoints (differentepistemic architectures) but also for level-of-detail - zooming in tosome (reductionist) model, or retreating to some level of abstraction.Technology (that is processable - i.e. usually digital) can help withthis - indeed, statistics, visualisation, modeling in general, ortowers of models, are all about this.

losing detail is not necessarily loss of knowledge - indeed, theability to ignore detail (see the wood for the trees, or the aforesaidabstraction process) is one of the more useful human (cognitive?)skills.